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The Five Regularities in the Financial Market – Price Action and Pattern Trading Course

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3. The Five Regularities in the Financial Market

 

The Financial Market is the place where different investors are trading securities

like equities, bonds, currencies and derivatives. It is the market place to facilitate

the exchange of securities between buyers and sellers. Loosely speaking, the

financial market works like the auction market where buyers enter competitive

bids  and  where  sellers  enter  competitive  offers  at  the  same  time.  However,

unlike  auction  market,  in  the  financial  market  securities  are  often  traded

without  delivering  actual  physical  goods.  Although  some  companies  can  use

financial market to hedge their physical positions, in this book, we will assume

that you are more of speculator who wants to profit from the market dynamics.

Various   buyers   and   sellers   with   different   attributes,   different   geographic

location,  different  purchasing  power  and  different  financial  goals,  forms  the

daily transactions  of the financial market. Therefore, the dynamics of financial

market can be represented as the crowd behaviour. It is not necessarily perfectly

rational  place  but  the  fundamentals  play  some  important  role  behind  the

market dynamics up to some degree.

For traders  and investors,  it is important to develop the  right trading  strategy

for the market.  Good trading strategy never comes blindly. Understanding the

underlying dynamics for the financial market is the important requirement to

build  a  solid  trading  strategy.  Then,  what  is  the  underlying  dynamics  for  the

financial  market  and  how  can  we  study  them  to  benefit  our  trading  and

investment?  Scientists  had  a  strong  interest  in  the  dynamics  of  the  financial

market  for many decades. They have extensively studied the dynamics of the

financial  price  series  in  the  Stock  and  Forex  market.  The  simplest  but  most

effective way to study the dynamics  might be the  decomposition approach.  In

decomposition, literarily we are breaking down some complex system into the

simple  and  digestible  bits.  Then  we  use  this  decomposed  bits  to  predict  the

behaviour of the complex system.

When we apply the decomposing technique for price series, the price series can

be decomposed  into several sub  price patterns. In fact, the  sub  price patterns

are  the  regularities  that  constitute  the  dynamics  of  the  financial  price  series

(Figure 3-1). For trading and investment, we make use of the knowledge of these

regularities to predict up or down movement of the financial market.  All  the

known  trading  strategies,  including  simple  and  complex  ones,  are  based  on

some of these regularities  existing in the price series.  Remember that none of

trading strategies is merely created to offer you just some luck or based on some

random theory.

 

 

Figure 3-1: The concept of the decomposition for the financial price series.

 

In Figure 3-1,  what could be the pattern 1, pattern 2, pattern 3 and pattern N

making up the real world financial price series? Yet, many different version of

decomposition techniques  exist to describe the price patterns  in the financial

market. Among them, Gardner’s version considers the trend and seasonality as

the main underlying components of the price series data (Gardner, 1987, p175).

Many  traders  are  already  familiar  with  trend  in  the  financial  markets.  For

example,  many  technical  indicators  like  moving  average  and  MACD  were

developed  to  visualize  trend  in  the  financial  markets.  Seasonality  is  literally

seasonal fluctuations in the market. It is also used by many traders. For example,

because  the  sales  of  Ice  Creams  increase  during  summer,  stock  price  for  Ice

Creams Company  can go up  due to the increased profits  during summer.  This

sort of patterns will make up the seasonal fluctuations.

 

The Gardner’s framework is intuitive and easy to understand because trend and

seasonality   are   the   backbone   of   many   analysis   techniques   used  for   the

univariate price series  in many  scientific fields. Although Gardner’s framework

does  not  mention  about  random  process  explicitly,  his  framework  already

assumed that any price series include some random process.

Depending   on   their   underlying   dynamics,   the   price   series   can  show   the

multitude  of  behaviours  because  real  world  price  series  are  made  up  from

different magnitude  of each  price pattern.  For example, sometimes, the price

series can exhibit strong trend without seasonality and vice versa. Sometimes

the price series can exhibit some trend with some seasonality. In the Gardner’s

trend-seasonality framework, we can generate twelve different behaviour of the

price series  by  combining the  basic  trend  and  seasonal  patterns  as  shown  in

Figure 3-2.  Scientist  uses  this framework  to  categorize  many real world  price

series data set for prediction purpose. Then, what is the practical use of the Price

Pattern  Table  in  Figure  3-2  for  traders?  As  a  trader,  we  can  develop  trading

strategies to capture these price patterns within the price series.  For example,

most of technical indicators are  created to capture trend pattern  in the price

series. Price patterns in price series are regularities, which help us to predict the

price series  into the future.  Financial trading is based on our prediction for the

future market. We buy EURUSD because we predict that EURUSD have the high

chance to go up. We sell EURUSD because we predict that EURUSD have the high

chance to go down.  If we understand  the existing regularities  of the financial

market  better, then we will likely  make better trading and investment decision

too.

 

 

Figure  3-2:  The  original  Gardner’s  table  to  visualize  the  characteristics  of

different time series data  (Gardner, 1987, p175).  Gardner assumed the three

components including randomness, trend and seasonality in this table.

 

In spite of the fact that trend and seasonality  are the  important price patterns

in the financial market, practically the entire financial market will not fit to this

trend-seasonality framework alone. If the market was so predictable with these

two  components  only,  then  traders  and  investors  were  able  to  make  money

much easier. Maybe you can also take advantage on buying shares of Ice Cream

Company during April and selling them late August.  If the pattern is there, then

 

you  should  do  that.  However,  in  the  highly  competitive  and  liquid  financial

market, this is not the case.  In many cases, the trend and seasonality might  be

the less significant components  in the financial price series  in the Stock  Market

and  Forex  in  comparison  to  the  data  obtained  from  the  business  and  social

studies. The Gardner’s trend and seasonal framework can work well for business

and  some  social  data  set  but  it  might  be  oversimplified  for  the  case  of  the

financial markets.

Instead of  the two components framework  with  trend and seasonality,  in this

book,  we  propose  the  three  components  framework.  The  three  components

include  Equilibrium  process,  Wave  process  and  Fractal-Wave  process.  These

three  components can serve to conceptualize the basic  price patterns existing

in the financial price series. Just like the trend and seasonal components in the

Gardner’s framework, these three components are the building blocks to explain

more  complex  price  patterns  in  the  financial  price  series  and  to  predict  the

future movement of the price series.  Just to convey our  idea, we will explain

these three  components in brief, before we  expand  each in more details from

the next chapter.

The Equilibrium process is equivalent to the trend in the Gardener’s framework.

However,  it  is  also the  same  term “equilibrium”  used in  the  supply-  demand

economic theory.  Literarily it is the market force moving the price to release the

unbalance  between  supply  and  demand.  Wave  process  is  any  cyclic  patterns

repeating  in  the  fixed  time  interval.  Wave  process  includes  the  concepts  of

additive  and  multiplicative  seasonality  in  the  Gardner’s  model.  Furthermore,

Wave process includes other complex cyclic behaviour, which can  be described

with the multiple of combined sine and cosine waves.  Finally, the Fractal-Wave

process is  the representation of  the Fractal geometry in the  time dimension.

 

Therefore,  it  is  the  self-similar  process  repeating  in  different  scales.  In  plain

language,  Fractal-Wave  process  refers to  the repeating  patterns  with  varying

scales. For example, trader might remember that the price patterns in the S&P

500 before 2008 financial crisis. He can come across the similar price patterns in

lower timeframe or in other instruments.  Because he has already seen that the

price  pattern  led  to  the  huge  bearish  movement  for  S&P500  before  2008

financial crisis, he would take the  sell action again whenever he recognize the

similar patterns from lower timeframe or from other instruments.

Just as Gardner visualized the possible combinations of trend and seasonality in

three columns in Figure 3-2, we can visualize the possible combinations of these

three  components  in five  columns.  In Figure 3-3, first three columns including

Equilibrium Process (=trend), Additive Seasonality and Multiplicative Seasonality

are identical to the Gardner’s three columns. Fourth column includes any simple

and complex cyclic patterns, which can be described with the combined sine and

cosine waves. Fifth column describes the Fractal-Wave process with Equilibrium

process. Each column represents a distinctive regularity with its own behaviour.

We can describe the five columns as the five regularities in the financial market

(Figure 3-3 and Figure 3-4).

One most obvious distinction among the five regularities is that each regularity

has the distinctive range of number of cycle periods as shown in Figure 3-5.  In

general,  Second  and  Third  Regularity  have  very  few  cycle  periods.  Fourth

Regularity tends to have more cycles but the number of cycles is still finite. The

Fifth Regularity can be characterized by the infinite number of cycles  because

the  repeating  patterns  can  have  the  infinitely  varying  scales  within  the  price

series. Therefore,  it becomes very clear that we  need  to use different tactics

when we deal with each regularities.

 

Especially, the fifth regularity is the underlying process behind many horizontal

and diagonal price pattern used by traders. The horizontal and diagonal price

pattern can include the popular price patterns like support, resistance, harmonic

patterns, Elliott Wave patterns, Triangle, Wedge and Channels, etc.  This book

mainly focuses for  the fifth regularity because the fifth regularity is the main

price dynamics behind many price action and pattern trading strategies. In the

book, we want to help you to understand the clear difference between this fifth

regularity and the rest. We will focus to cover the practical trading knowledge

for this  fifth  regularity.  Finally,  we will  help you to learn  the price action and

pattern trading strategy in the practical level throughout this book.

There are  many different data in the Stock  Market and Forex. Remember that

different players are participating in the different markets. Each financial price

series will be played by different players with different attributes and different

psychologies. Therefore, each price series can have their own dynamics because

they possess different price patterns in different magnitude. For example, some

stock market price series  can possess  much stronger Equilibrium process than

currency price  series in  the Forex.  Practically speaking, the most of the price

series  in  the  Stock  market  and  Forex  will  have  either  the  mixed  effects  of

Equilibrium  process  and  Wave  process  or  the  mixed  effects  of  Equilibrium

process   and   Fractal-Wave   process.             This   means   that   they   are   a        highly

complicated system representing the crowd behaviour of millions of people.

Once again, the main purpose of this taxonomy is to identify regularities existing

in  the  financial  price  series. Therefore,  traders  can  make  prediction  for  their

trading. The five regularities framework can be used to build any trading strategy

for  different financial market. For example, there is no need to apply  hammer

when the entire house was  built with bolts and nuts.  In addition, the medical

 

doctor will  prescribe you the  medicine for  cold when your symptoms are very

close to other patients having cold.  Likewise, if the financial price series exhibit

strong trend and multiple cycles, then you should just apply the right tools to

capture the strong trend and multiple cycles for your trading. If you are applying

the tool to capture trend only or if you are applying the tool to capture cycles

only,  then  you  will  be  underestimating  the  market.  Therefore,  you  will  be

suffering  more  than  enjoying  the  profits.  Practically  speaking,  trader  should

know what regularities they are dealing with and what tools they need to apply

to capture those regularities.

From  next  chapter,  we  will  describe  the  sub  price  patterns  under  these  five

regularities  in  details  (Figure  3-6).   Especially,  we  will  focus  to  explain  the

combined price patterns like Equilibrium Wave process and Equilibrium Fractal-

Wave process. It is because the price patterns in the real world financial markets

are likely to be one of these complex  patterns. We will try our best to visualize

each price patterns with example. However, for Forex and Stock market, it is not

easy to find them  showing simple trend pattern or seasonal pattern alone. As

we  have  mentioned  before,  highly  competitive  and  liquid  market  are  likely

showing more complex patterns  like  Equilibrium Wave process or  Equilibrium

Fractal-Wave  process.  Therefore,  when  we  explain  an  obviously  simple  price

patterns, then we might use some data set not from the Forex or stock markets

because  it is difficult to find Stock or Forex market data showing trend pattern

alone.  For  example,  in  explaining  the  Equilibrium  price  patterns,  we  use  UK

housing price to show you how  the typical Equilibrium  dominated price series

look like. Sometimes we might use some synthetic price series to visualize some

price patterns in Figure 3-6.

 

After we have covered all the sub price patterns in next few chapters, we will

move to the practical part focusing on the fifth regularity for your trading. The

fifth regularity is the least understood but most confused price patterns among

trader comparing to the rest of the regularities. Especially, the characteristic of

the  infinite cycle period tells us that many technical indicator,  we  were  using

without any doubt,  can  reduce your  profitability  or at least  they can act as  an

inefficient  element  in  your  trading.  Simply  many  technical  indicators  are  not

designed to deal with the  infinity  but they were designed rather to reduce the

noise  from  the  price  series  by  smoothing  or  averaging.  When  you  do  not

understand nature  of  wave  in  the price series,  these technical  indicators  can

take away many good trading opportunities from you.

In addition, traders observe many horizontal and diagonal price patterns every

day because of the Equilibrium Fractal Wave propagation. We want to bring the

unified view or just one simple concept encapsulating these price patterns for

both educational and practical trading purpose. The commonly used term “raw

price action” among the price action trading community does not provide much

explanation  for  beginners  or  any  relation  to  the  already  established  trading

practice and concepts.

In doing so, first, we will help you on how to identify those price patterns using

the  Peak  Trough  Analysis  technique  from  your  charts.  We  present  several

different Peak Trough Analysis technique for your trading. Please note that we

provide free Peak Trough Analysis tool in our website. Second, we will presents

the actual trading strategy  especially  designed  to deal with the  infinity  of the

fifth regularity. We will look at the increasingly popular trading strategies for this

purpose.    We  will  start  with  the  support  and  resistance  to  introduce  some

fundamental  trading  knowledge  on  the  price  patterns.  Then  we  will  further

 

expand it with the popular trading strategies like Harmonic Pattern, Elliott Wave,

Triangle and Wedge patterns. These trading strategies are over 80 years old and

used by many reputable traders in the world. Several traders thought that these

strategies are connected but it is difficult to find the literature level of claim yet.

We show that these advanced trading strategies can be explained in one notion,

the fifth  regularity  (Figure 3-7).  At the same time, we will reveal  the powerful

trading recipes you can use for your practical trading in this book.

 

 

Figure 3-3: Five Regularities and their sub price patterns with inclining trends.

Each  pattern  can  be  referenced  using  their  row  and  column  number.  For

example,  exponential  trend  pattern  in  the  third  row  and first  column  can  be

referenced as  Pattern (3, 1) in this table.

 

 

Figure 3-4:  Five Regularities and their sub price patterns with declining trend.

Each price pattern can be referenced using their row and column  number. For

example,  exponential  trend  pattern  in  the  third row  and first  column  can  be

referenced as Pattern (3, 1) in this table.

 

 

 

Figure 3-5: Visualizing number of cycle periods  for  the five regularities.  Please

note that this is only the conceptual  demonstration  and the number of cycles

for second, third and fourth regularity can vary for different price series.